Distributed Formation Control of Double-Integrator Systems via Adaptive CBFs with Dynamic Safety Margins
Bibliographic record
Abstract
This paper presents the design of a safe formation control approach for homogeneous multirobot systems with double-integrator dynamics-a model integrating inertial dynamics, which are essential for accurate control during high-speed manoeuvres.To ensure safe navigation, a real-time control scheme is proposed, in which formation constraints and collision avoidance are formulated as control barrier function (CBF) conditions within a quadratic program (QP).Forward invariance of the safe formation set is achieved by guaranteeing a minimum safety margin, preserving formation geometry, and forcing the system to stay in the safe set.Collision-free transitions between different shapes are achieved through CBF.Numerical simulations in cluttered, dynamic environments demonstrate that our approach preserves formation integrity and prevents collisions without sacrificing agility.These results demonstrate the advantages of combining elastic formation flexibility with safety guarantees, which constitutes a promising approach for agile and scalable coordination.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".